14,095 research outputs found
Modeling of dilution jet flowfields
The present paper will compare temperature field measurements from selected cases in these investigations with distributions calculated with an empirical model based on assumed vertical profile similarity and superposition and with a 3-D elliptic code using a standard K-E turbulence model. The results will show the capability (or lack thereof) of the models to predict the effects of the principle flow and geometric variables
On modeling dilution jet flowfields
This paper compares temperature field measurements from selected experiments on a single row, and opposed rows, of jets injected into a ducted crossflow with profiles calculated using an empirical model based on assumed vertical profile similarity and superposition, and distributions calculated with a 3-D elliptic code using a standard K-E turbulence model. The empirical model predictions are very good within the range of the generating experiments, and the numerical model resultings, although exhibiting too little mixing, correctly describe the effects of the principal flow and geometric variables
Qualitative System Identification from Imperfect Data
Experience in the physical sciences suggests that the only realistic means of
understanding complex systems is through the use of mathematical models.
Typically, this has come to mean the identification of quantitative models
expressed as differential equations. Quantitative modelling works best when the
structure of the model (i.e., the form of the equations) is known; and the
primary concern is one of estimating the values of the parameters in the model.
For complex biological systems, the model-structure is rarely known and the
modeler has to deal with both model-identification and parameter-estimation. In
this paper we are concerned with providing automated assistance to the first of
these problems. Specifically, we examine the identification by machine of the
structural relationships between experimentally observed variables. These
relationship will be expressed in the form of qualitative abstractions of a
quantitative model. Such qualitative models may not only provide clues to the
precise quantitative model, but also assist in understanding the essence of
that model. Our position in this paper is that background knowledge
incorporating system modelling principles can be used to constrain effectively
the set of good qualitative models. Utilising the model-identification
framework provided by Inductive Logic Programming (ILP) we present empirical
support for this position using a series of increasingly complex artificial
datasets. The results are obtained with qualitative and quantitative data
subject to varying amounts of noise and different degrees of sparsity. The
results also point to the presence of a set of qualitative states, which we
term kernel subsets, that may be necessary for a qualitative model-learner to
learn correct models. We demonstrate scalability of the method to biological
system modelling by identification of the glycolysis metabolic pathway from
data
The Mass-Loss Return From Evolved Stars to The Large Magellanic Cloud VI: Luminosities and Mass-Loss Rates on Population Scales
We present results from the first application of the Grid of Red Supergiant
and Asymptotic Giant Branch ModelS (GRAMS) model grid to the entire evolved
stellar population of the Large Magellanic Cloud (LMC). GRAMS is a pre-computed
grid of 80,843 radiative transfer (RT) models of evolved stars and
circumstellar dust shells composed of either silicate or carbonaceous dust. We
fit GRAMS models to ~30,000 Asymptotic Giant Branch (AGB) and Red Supergiant
(RSG) stars in the LMC, using 12 bands of photometry from the optical to the
mid-infrared. Our published dataset consists of thousands of evolved stars with
individually determined evolutionary parameters such as luminosity and
mass-loss rate. The GRAMS grid has a greater than 80% accuracy rate
discriminating between Oxygen- and Carbon-rich chemistry. The global dust
injection rate to the interstellar medium (ISM) of the LMC from RSGs and AGB
stars is on the order of 1.5x10^(-5) solar masses/yr, equivalent to a total
mass injection rate (including the gas) into the ISM of ~5x10^(-3) solar
masses/yr. Carbon stars inject two and a half times as much dust into the ISM
as do O-rich AGB stars, but the same amount of mass. We determine a bolometric
correction factor for C-rich AGB stars in the K band as a function of J - K
color, BC(K) = -0.40(J-K)^2 + 1.83(J-K) + 1.29. We determine several IR color
proxies for the dust mass-loss rate (MLR) from C-rich AGB stars, such as log
(MLR) = (-18.90)/((K-[8.0])+3.37)-5.93. We find that a larger fraction of AGB
stars exhibiting the `long-secondary period' phenomenon are O-rich than stars
dominated by radial pulsations, and AGB stars without detectable mass-loss do
not appear on either the first-overtone or fundamental-mode pulsation
sequences.Comment: 19 pages, 19 figure
Experiments in dilution jet mixing
Experimental results are given on the mixing of a single row of jets with an isothermal mainstream in a straight duct, to include flow and geometric variations typical of combustion chambers in gas turbine engines. The principal conclusions reached from these experiments were: at constant momentum ratio, variations in density ratio have only a second-order effect on the profiles; a first-order approximation to the mixing of jets with a variable temperature mainstream can be obtained by superimposing the jets-in-an isothermal-crossflow and mainstream profiles; flow area convergence, especially injection-wall convergence, significantly improves the mixing; for opposed rows of jets, with the orifice centerlines in-line, the optimum ratio of orifice spacing to duct height is one half of the optimum value for single side injection at the same momentum ratio; and for opposed rows of jets, with the orifice centerlines staggered, the optimum ratio of orifice spacing to duct height is twice the optimum value for single side injection at the same momentum ratio
Method of complex paths and general covariance of Hawking radiation
We apply the technique of complex paths to obtain Hawking radiation in
different coordinate representations of the Schwarzschild space-time. The
coordinate representations we consider do not possess a singularity at the
horizon unlike the standard Schwarzschild coordinate. However, the event
horizon manifests itself as a singularity in the expression for the
semi-classical action. This singularity is regularized by using the method of
complex paths and we find that Hawking radiation is recovered in these
coordinates indicating the covariance of Hawking radiation. This also shows
that there is no correspondence between the particles detected by the model
detector and the particle spectrum obtained by the quantum field theoretic
analysis -- a result known in other contexts as well.Comment: 9 pages, uses MPLA Style file, Accepted for publication in Mod. Phys.
Letts.
Bubbling route to strange nonchaotic attractor in a nonlinear series LCR circuit with a nonsinusoidal force
We identify a novel route to the birth of a strange nonchaotic attractor
(SNA) in a quasiperiodically forced electronic circuit with a nonsinusoidal
(square wave) force as one of the quasiperiodic forces through numerical and
experimental studies. We find that bubbles appear in the strands of the
quasiperiodic attractor due to the instability induced by the additional square
wave type force. The bubbles then enlarge and get increasingly wrinkled as a
function of the control parameter. Finally, the bubbles get extremely wrinkled
(while the remaining parts of the strands of the torus remain largely
unaffected) resulting in the birth of the SNA which we term as the
\emph{bubbling route to SNA}. We characterize and confirm this birth from both
experimental and numerical data by maximal Lyapunov exponents and their
variance, Poincar\'e maps, Fourier amplitude spectra and spectral distribution
function. We also strongly confirm the birth of SNA via the bubbling route by
the distribution of the finite-time Lyapunov exponents.Comment: 11 pages. 11 figures, Accepted for publication in Phys. Rev.
Tribological properties of sintered polycrystalline and single crystal silicon carbide
Tribological studies and X-ray photoelectron spectroscopy analyses were conducted with sintered polycrystalline and single crystal silicon carbide surfaces in sliding contact with iron at various temperatures to 1500 C in a vacuum of 30 nPa. The results indicate that there is a significant temperature influence on both the friction properties and the surface chemistry of silicon carbide. The main contaminants on the as received sintered polycrystalline silicon carbide surfaces are adsorbed carbon, oxygen, graphite, and silicon dioxide. The surface revealed a low coefficient of friction. This is due to the presence of the graphite on the surface. At temperatures of 400 to 600 C graphite and copious amount of silicon dioxide were observed on the polycrystalline silicon carbide surface in addition to silicon carbide. At 800 C, the amount of the silicon dioxide decreased rapidly and the silicon carbide type silicon and carbon peaks were at a maximum intensity in the XPS spectra. The coefficients of friction were high in the temperature range 400 to 800 C. Small amounts of carbon and oxygen contaminants were observed on the as received single crystal silicon carbide surface below 250 C. Silicon carbide type silicon and carbon peaks were seen on the silicon carbide in addition to very small amount of graphite and silicon dioxide at temperatures of 450 to 800 C
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